New Fuzzy-Clustering Algorithm for Data Stream

Sun Li-juan; Chen Xiao-dong; Han Chong; Guo Jian

doi:10.11999/JEIT141415

Volume 37 Issue 7

Jul. 2015

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Article Navigation > Journal of Electronics & Information Technology > 2015 > 37(7): 1620-1625

Sun Li-juan, Chen Xiao-dong, Han Chong, Guo Jian. New Fuzzy-Clustering Algorithm for Data Stream[J]. Journal of Electronics & Information Technology, 2015, 37(7): 1620-1625. doi: 10.11999/JEIT141415

Citation:

Sun Li-juan, Chen Xiao-dong, Han Chong, Guo Jian. New Fuzzy-Clustering Algorithm for Data Stream[J]. Journal of Electronics & Information Technology, 2015, 37(7): 1620-1625. doi: 10.11999/JEIT141415

Sun Li-juan, Chen Xiao-dong, Han Chong, Guo Jian. New Fuzzy-Clustering Algorithm for Data Stream[J]. Journal of Electronics & Information Technology, 2015, 37(7): 1620-1625. doi: 10.11999/JEIT141415

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New Fuzzy-Clustering Algorithm for Data Stream

doi: 10.11999/JEIT141415

1.
2.
(College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210003, China)

Received Date: 2014-11-05
Rev Recd Date: 2015-03-20
Publish Date: 2015-07-19

Abstract

Abstract

There is a great challenge in the data stream clustering due to a limitation of time and space. In order to solve this problem, a new fuzzy-clustering algorithm, called Weight Decay Streaming Micro Clustering (WDSMC), is presented in this paper. The algorithm uses a reformed weighted Fuzzy C-Means (FCM) algorithm, and improves the quality of clustering by the structures of micro-clusters and weight-decay. Experimental results show that this algorithm has better accuracy than Stream Weight Fuzzy C-Means (SWFCM) and StreamKM++ algorithm.
- Data mining,
- Data stream,
- Fuzzy C-Means (FCM),
- Weight decay,
- Micro-clustering

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References(20)

References

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